Drug-Induced Fatty Liver Disease (DIFLD): A Comprehensive Analysis of Clinical, Biochemical, and Histopathological Data for Mechanisms Identification and Consistency with Current Adverse Outcome Pathways.

Drug induced fatty liver disease (DIFLD) is a form of drug-induced liver injury (DILI), which can also be included in the more general metabolic dysfunction-associated steatotic liver disease (MASLD), which specifically refers to the accumulation of fat in the liver unrelated to alcohol intake. A bi-directional relationship between DILI and MASLD is likely to exist: while certain drugs can cause MASLD by acting as pro-steatogenic factors, MASLD may make hepatocytes more vulnerable to drugs. Having a pre-existing MASLD significantly heightens the likelihood of experiencing DILI from certain medications. Thus, the prevalence of steatosis within DILI may be biased by pre-existing MASLD, and it can be concluded that the genuine true incidence of DIFLD in the general population remains unknown. In certain individuals, drug-induced steatosis is often accompanied by concomitant injury mechanisms such as oxidative stress, cell death, and inflammation, which leads to the development of drug-induced steatohepatitis (DISH). DISH is much more severe from the clinical point of view, has worse prognosis and outcome, and resembles MASH (metabolic-associated steatohepatitis), as it is associated with inflammation and sometimes with fibrosis. A literature review of clinical case reports allowed us to examine and evaluate the clinical features of DIFLD and their association with specific drugs, enabling us to propose a classification of DIFLD drugs based on clinical outcomes and pathological severity: Group 1, drugs with low intrinsic toxicity (e.g., ibuprofen, naproxen, acetaminophen, irinotecan, methotrexate, and tamoxifen), but expected to promote/aggravate steatosis in patients with pre-existing MASLD; Group 2, drugs associated with steatosis and only occasionally with steatohepatitis (e.g., amiodarone, valproic acid, and tetracycline); and Group 3, drugs with a great tendency to transit to steatohepatitis and further to fibrosis. Different mechanisms may be in play when identifying drug mode of action: (1) inhibition of mitochondrial fatty acid ß-oxidation; (2) inhibition of fatty acid transport across mitochondrial membranes; (3) increased de novo lipid synthesis; (4) reduction in lipid export by the inhibition of microsomal triglyceride transfer protein; (5) induction of mitochondrial permeability transition pore opening; (6) dissipation of the mitochondrial transmembrane potential; (7) impairment of the mitochondrial respiratory chain/oxidative phosphorylation; (8) mitochondrial DNA damage, degradation and depletion; and (9) nuclear receptors (NRs)/transcriptomic alterations. Currently, the majority of, if not all, adverse outcome pathways (AOPs) for steatosis in AOP-Wiki highlight the interaction with NRs or transcription factors as the key molecular initiating event (MIE). This perspective suggests that chemical-induced steatosis typically results from the interplay between a chemical and a NR or transcription factors, implying that this interaction represents the primary and pivotal MIE. However, upon conducting this exhaustive literature review, it became evident that the current AOPs tend to overly emphasize this interaction as the sole MIE. Some studies indeed support the involvement of NRs in steatosis, but others demonstrate that such NR interactions alone do not necessarily lead to steatosis. This view, ignoring other mitochondrial-related injury mechanisms, falls short in encapsulating the intricate biological mechanisms involved in chemically induced liver steatosis, necessitating their consideration as part of the AOP's map road as well.

A quantitative weight-of-evidence method for confidence assessment of adverse outcome pathway networks: A case study on chemical-induced liver steatosis.

The field of chemical toxicity testing is undergoing a transition to overcome the limitations of in vivo experiments. This evolution involves implementing innovative non-animal approaches to improve predictability and provide a more precise understanding of toxicity mechanisms. Adverse outcome pathway (AOP) networks are pivotal in organizing existing mechanistic knowledge related to toxicological processes. However, these AOP networks are dynamic and require regular updates to incorporate the latest data. Regulatory challenges also persist due to concerns about the reliability of the information they offer. This study introduces a generic Weight-of-Evidence (WoE) scoring method, aligned with the tailored Bradford-Hill criteria, to quantitatively assess the confidence levels in key event relationships (KERs) within AOP networks. We use the previously published AOP network on chemical-induced liver steatosis, a prevalent form of human liver injury, as a case study. Initially, the existing AOP network is optimized with the latest scientific information extracted from PubMed using the free SysRev platform for artificial intelligence (AI)-based abstract inclusion and standardized data collection. The resulting optimized AOP network, constructed using Cytoscape, visually represents confidence levels through node size (key event, KE) and edge thickness (KERs). Additionally, a Shiny application is developed to facilitate user interaction with the dataset, promoting future updates. Our analysis of 173 research papers yielded 100 unique KEs and 221 KERs among which 72 KEs and 170 KERs, respectively, have not been previously documented in the prior AOP network or AOP-wiki. Notably, modifications in de novo lipogenesis, fatty acid uptake and mitochondrial beta-oxidation, leading to lipid accumulation and liver steatosis, garnered the highest KER confidence scores. In conclusion, our study delivers a generic methodology for developing and assessing AOP networks. The quantitative WoE scoring method facilitates in determining the level of support for KERs within the optimized AOP network, offering valuable insights into its utility in both scientific research and regulatory contexts. KERs supported by robust evidence represent promising candidates for inclusion in an in vitro test battery for reliably predicting chemical-induced liver steatosis within regulatory frameworks.

Novel clinical phenotypes, drug categorization, and outcome prediction in drug-induced cholestasis: Analysis of a database of 432 patients developed by literature review and machine learning support.

BACKGROUND: Serum transaminases, alkaline phosphatase and bilirubin are common parameters used for DILI diagnosis, classification, and prognosis. However, the relevance of clinical examination, histopathology and drug chemical properties have not been fully investigated. As cholestasis is a frequent and complex DILI manifestation, our goal was to investigate the relevance of clinical features and drug properties to stratify drug-induced cholestasis (DIC) patients, and to develop a prognosis model to identify patients at risk and high-concern drugs. METHODS: DIC-related articles were searched by keywords and Boolean operators in seven databases. Relevant articles were uploaded onto Sysrev, a machine-learning based platform for article review and data extraction. Demographic, clinical, biochemical, and liver histopathological data were collected. Drug properties were obtained from databases or QSAR modelling. Statistical analyses and logistic regressions were performed. RESULTS: Data from 432 DIC patients associated with 52 drugs were collected. Fibrosis strongly associated with fatality, whereas canalicular paucity and ALP associated with chronicity. Drugs causing cholestasis clustered in three major groups. The pure cholestatic pattern divided into two subphenotypes with differences in prognosis, canalicular paucity, fibrosis, ALP and bilirubin. A predictive model of DIC outcome based on non-invasive parameters and drug properties was developed. Results demonstrate that physicochemical (pKa-a) and pharmacokinetic (bioavailability, CYP2C9) attributes impinged on the DIC phenotype and allowed the identification of high-concern drugs. CONCLUSIONS: We identified novel associations among DIC manifestations and disclosed novel DIC subphenotypes with specific clinical and chemical traits. The developed predictive DIC outcome model could facilitate DIC prognosis in clinical practice and drug categorization.

Defined D-hexapeptides bind CUG repeats and rescue phenotypes of myotonic dystrophy myotubes in a Drosophila model of the disease.

In Myotonic Dystrophy type 1 (DM1), a non-coding CTG repeats rare expansion disease; toxic double-stranded RNA hairpins sequester the RNA-binding proteins Muscleblind-like 1 and 2 (MBNL1 and 2) and trigger other DM1-related pathogenesis pathway defects. In this paper, we characterize four D-amino acid hexapeptides identified together with abp1, a peptide previously shown to stabilize CUG RNA in its single-stranded conformation. With the generalized sequence cpy(a/t)(q/w)e, these related peptides improved three MBNL-regulated exon inclusions in DM1-derived cells. Subsequent experiments showed that these compounds generally increased the relative expression of MBNL1 and its nuclear-cytoplasmic distribution, reduced hyperactivated autophagy, and increased the percentage of differentiated (Desmin-positive) cells in vitro. All peptides rescued atrophy of indirect flight muscles in a Drosophila model of the disease, and partially rescued muscle function according to climbing and flight tests. Investigation of their mechanism of action supports that all four compounds can bind to CUG repeats with slightly different association constant, but binding did not strongly influence the secondary structure of the toxic RNA in contrast to abp1. Finally, molecular modeling suggests a detailed view of the interactions of peptide-CUG RNA complexes useful in the chemical optimization of compounds.

Myotonic dystrophy: candidate small molecule therapeutics.

Myotonic dystrophy type 1 (DM1) is a rare multisystemic neuromuscular disorder caused by expansion of CTG trinucleotide repeats in the noncoding region of the DMPK gene. Mutant DMPK transcripts are toxic and alter gene expression at several levels. Chiefly, the secondary structure formed by CUGs has a strong propensity to capture and retain proteins, like those of the muscleblind-like (MBNL) family. Sequestered MBNL proteins cannot then fulfill their normal functions. Many therapeutic approaches have been explored to reverse these pathological consequences. Here, we review the myriad of small molecules that have been proposed for DM1, including examples obtained from computational rational design, HTS, drug repurposing, and therapeutic gene modulation.

In Vivo Imaging of Natural Killer Cell Trafficking in Tumors.

UNLABELLED: Natural killer cells (NKs) are important effectors of the innate immune system, with marked antitumor activity. Imaging NK trafficking in vivo may be relevant to following up the efficacy of new therapeutic approaches aiming at increasing tumor-infiltrating NKs (TINKs). The specific aims of present study were to efficiently target NKs using a 99mTc-anti-CD56 and to image human NK trafficking in SCID mice bearing human cancer. METHODS: The anti-CD56 monoclonal antibody (mAb) was radiolabeled with 99mTc, and in vitro quality controls were performed to test labeling efficiency, stability, and binding affinity to CD56. In vivo biodistribution was determined by injecting 5.5 MBq (104 ng) of radiolabeled antibody in the tail vein of SCID mice, which were then sacrificed at 1, 3, 6, and 24 h after injection. Targeting experiments were performed on 2 groups of SCID mice inoculated subcutaneously with increasing numbers of human NKs in the right thigh (from 2.5×10(6) to 40×10(6)) and human granulocytes (CD56-) or anaplastic thyroid cancer (ARO) cells in the contralateral thigh as control. TINK trafficking imaging was achieved by injecting 5.5 MBq of 99mTc-anti-CD56 mAb in SCID mice bearing ARO tumor xenografts in the right thigh, 24 h after being reconstituted with 10(5), 10(6), or 10(7) human NKs. RESULTS: Anti-CD56 mAb was radiolabeled, achieving a radiochemical purity of more than 97% and a specific activity of 3,700 MBq/mg and retaining biochemical integrity and binding activity. In vivo studies revealed physiologic uptake in the liver and kidneys. Targeting experiments confirmed the specificity of labeled antibody to CD56+ cells. Human NK cells injected in CD1 nude mice accumulated in the ARO tumors within 24 h and were imaged as early as 3 h after intravenous administration of (99m)Tc-anti-CD56. CONCLUSION: 99mTc-anti-CD56 is a promising tool for in vivo imaging of TINK cell trafficking.